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» How to process uncertainty in machine learning
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TREC
2004
13 years 9 months ago
Feature Generation, Feature Selection, Classifiers, and Conceptual Drift for Biomedical Document Triage
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 7 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
JMLR
2008
129views more  JMLR 2008»
13 years 7 months ago
Finite-Time Bounds for Fitted Value Iteration
In this paper we develop a theoretical analysis of the performance of sampling-based fitted value iteration (FVI) to solve infinite state-space, discounted-reward Markovian decisi...
Rémi Munos, Csaba Szepesvári
IDA
2009
Springer
13 years 5 months ago
Estimating Hidden Influences in Metabolic and Gene Regulatory Networks
We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory net...
Florian Blöchl, Fabian J. Theis
JMLR
2010
116views more  JMLR 2010»
13 years 2 months ago
Feature Selection, Association Rules Network and Theory Building
As the size and dimensionality of data sets increase, the task of feature selection has become increasingly important. In this paper we demonstrate how association rules can be us...
Sanjay Chawla